Overview

Brought to you by YData

Dataset statistics

Number of variables12
Number of observations100
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.5 KiB
Average record size in memory97.3 B

Variable types

Numeric1
Text10
DateTime1

Alerts

Index is uniformly distributed Uniform
Index has unique values Unique
Customer Id has unique values Unique
City has unique values Unique
Phone 1 has unique values Unique
Phone 2 has unique values Unique
Email has unique values Unique
Website has unique values Unique

Reproduction

Analysis started2025-03-19 05:40:35.039762
Analysis finished2025-03-19 05:40:37.245594
Duration2.21 seconds
Software versionydata-profiling vv4.12.1
Download configurationconfig.json

Variables

Index
Real number (ℝ)

Uniform  Unique 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean50.5
Minimum1
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size932.0 B
2025-03-19T11:10:37.473012image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5.95
Q125.75
median50.5
Q375.25
95-th percentile95.05
Maximum100
Range99
Interquartile range (IQR)49.5

Descriptive statistics

Standard deviation29.011492
Coefficient of variation (CV)0.57448499
Kurtosis-1.2
Mean50.5
Median Absolute Deviation (MAD)25
Skewness0
Sum5050
Variance841.66667
MonotonicityStrictly increasing
2025-03-19T11:10:37.810626image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.0%
64 1
 
1.0%
74 1
 
1.0%
73 1
 
1.0%
72 1
 
1.0%
71 1
 
1.0%
70 1
 
1.0%
69 1
 
1.0%
68 1
 
1.0%
67 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
1 1
1.0%
2 1
1.0%
3 1
1.0%
4 1
1.0%
5 1
1.0%
6 1
1.0%
7 1
1.0%
8 1
1.0%
9 1
1.0%
10 1
1.0%
ValueCountFrequency (%)
100 1
1.0%
99 1
1.0%
98 1
1.0%
97 1
1.0%
96 1
1.0%
95 1
1.0%
94 1
1.0%
93 1
1.0%
92 1
1.0%
91 1
1.0%

Customer Id
Text

Unique 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2025-03-19T11:10:38.321652image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length15
Median length15
Mean length15
Min length15

Characters and Unicode

Total characters1500
Distinct characters22
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique100 ?
Unique (%)100.0%

Sample

1st rowDD37Cf93aecA6Dc
2nd row1Ef7b82A4CAAD10
3rd row6F94879bDAfE5a6
4th row5Cef8BFA16c5e3c
5th row053d585Ab6b3159
ValueCountFrequency (%)
dd37cf93aeca6dc 1
 
1.0%
e35426ebdeceaff 1
 
1.0%
6f94879bdafe5a6 1
 
1.0%
5cef8bfa16c5e3c 1
 
1.0%
053d585ab6b3159 1
 
1.0%
2d08fb17ee273f4 1
 
1.0%
ea4d384dfdbbf77 1
 
1.0%
0e04afde9f225de 1
 
1.0%
c2de4deec489ae0 1
 
1.0%
8c2811a503c7c5a 1
 
1.0%
Other values (90) 90
90.0%
2025-03-19T11:10:38.989370image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
F 80
 
5.3%
e 76
 
5.1%
0 75
 
5.0%
8 74
 
4.9%
f 74
 
4.9%
2 74
 
4.9%
E 74
 
4.9%
D 73
 
4.9%
a 71
 
4.7%
1 71
 
4.7%
Other values (12) 758
50.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 663
44.2%
Lowercase Letter 422
28.1%
Uppercase Letter 415
27.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 75
11.3%
8 74
11.2%
2 74
11.2%
1 71
10.7%
6 69
10.4%
9 67
10.1%
3 66
10.0%
7 58
8.7%
4 58
8.7%
5 51
7.7%
Uppercase Letter
ValueCountFrequency (%)
F 80
19.3%
E 74
17.8%
D 73
17.6%
A 70
16.9%
B 61
14.7%
C 57
13.7%
Lowercase Letter
ValueCountFrequency (%)
e 76
18.0%
f 74
17.5%
a 71
16.8%
b 69
16.4%
c 67
15.9%
d 65
15.4%

Most occurring scripts

ValueCountFrequency (%)
Latin 837
55.8%
Common 663
44.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
F 80
9.6%
e 76
9.1%
f 74
8.8%
E 74
8.8%
D 73
8.7%
a 71
8.5%
A 70
8.4%
b 69
8.2%
c 67
8.0%
d 65
7.8%
Other values (2) 118
14.1%
Common
ValueCountFrequency (%)
0 75
11.3%
8 74
11.2%
2 74
11.2%
1 71
10.7%
6 69
10.4%
9 67
10.1%
3 66
10.0%
7 58
8.7%
4 58
8.7%
5 51
7.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1500
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
F 80
 
5.3%
e 76
 
5.1%
0 75
 
5.0%
8 74
 
4.9%
f 74
 
4.9%
2 74
 
4.9%
E 74
 
4.9%
D 73
 
4.9%
a 71
 
4.7%
1 71
 
4.7%
Other values (12) 758
50.5%

First Name
Text

Distinct93
Distinct (%)93.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2025-03-19T11:10:39.584962image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length10
Median length9
Mean length5.89
Min length3

Characters and Unicode

Total characters589
Distinct characters44
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique86 ?
Unique (%)86.0%

Sample

1st rowSheryl
2nd rowPreston
3rd rowRoy
4th rowLinda
5th rowJoanna
ValueCountFrequency (%)
sheryl 2
 
2.0%
tom 2
 
2.0%
shane 2
 
2.0%
sherry 2
 
2.0%
faith 2
 
2.0%
joanna 2
 
2.0%
lynn 2
 
2.0%
dakota 1
 
1.0%
roy 1
 
1.0%
linda 1
 
1.0%
Other values (83) 83
83.0%
2025-03-19T11:10:40.365809image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 72
12.2%
e 66
 
11.2%
n 53
 
9.0%
r 47
 
8.0%
i 45
 
7.6%
l 40
 
6.8%
o 27
 
4.6%
y 23
 
3.9%
t 21
 
3.6%
h 19
 
3.2%
Other values (34) 176
29.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 489
83.0%
Uppercase Letter 100
 
17.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 72
14.7%
e 66
13.5%
n 53
10.8%
r 47
9.6%
i 45
9.2%
l 40
8.2%
o 27
 
5.5%
y 23
 
4.7%
t 21
 
4.3%
h 19
 
3.9%
Other values (14) 76
15.5%
Uppercase Letter
ValueCountFrequency (%)
C 11
 
11.0%
S 10
 
10.0%
K 8
 
8.0%
L 8
 
8.0%
R 7
 
7.0%
J 7
 
7.0%
D 6
 
6.0%
F 5
 
5.0%
G 5
 
5.0%
A 5
 
5.0%
Other values (10) 28
28.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 589
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 72
12.2%
e 66
 
11.2%
n 53
 
9.0%
r 47
 
8.0%
i 45
 
7.6%
l 40
 
6.8%
o 27
 
4.6%
y 23
 
3.9%
t 21
 
3.6%
h 19
 
3.2%
Other values (34) 176
29.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 589
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 72
12.2%
e 66
 
11.2%
n 53
 
9.0%
r 47
 
8.0%
i 45
 
7.6%
l 40
 
6.8%
o 27
 
4.6%
y 23
 
3.9%
t 21
 
3.6%
h 19
 
3.2%
Other values (34) 176
29.9%

Last Name
Text

Distinct97
Distinct (%)97.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2025-03-19T11:10:40.882545image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length11
Median length9
Mean length5.94
Min length3

Characters and Unicode

Total characters594
Distinct characters46
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique94 ?
Unique (%)94.0%

Sample

1st rowBaxter
2nd rowLozano
3rd rowBerry
4th rowOlsen
5th rowBender
ValueCountFrequency (%)
greer 2
 
2.0%
mata 2
 
2.0%
foley 2
 
2.0%
bradshaw 1
 
1.0%
lutz 1
 
1.0%
bender 1
 
1.0%
downs 1
 
1.0%
peck 1
 
1.0%
mullen 1
 
1.0%
meyers 1
 
1.0%
Other values (87) 87
87.0%
2025-03-19T11:10:41.661253image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 61
 
10.3%
n 53
 
8.9%
e 51
 
8.6%
o 51
 
8.6%
r 44
 
7.4%
l 29
 
4.9%
s 29
 
4.9%
i 24
 
4.0%
t 20
 
3.4%
d 19
 
3.2%
Other values (36) 213
35.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 494
83.2%
Uppercase Letter 100
 
16.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 61
12.3%
n 53
10.7%
e 51
10.3%
o 51
10.3%
r 44
 
8.9%
l 29
 
5.9%
s 29
 
5.9%
i 24
 
4.9%
t 20
 
4.0%
d 19
 
3.8%
Other values (15) 113
22.9%
Uppercase Letter
ValueCountFrequency (%)
M 14
14.0%
H 12
12.0%
G 10
10.0%
B 8
 
8.0%
F 7
 
7.0%
C 6
 
6.0%
D 6
 
6.0%
S 5
 
5.0%
P 5
 
5.0%
L 4
 
4.0%
Other values (11) 23
23.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 594
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 61
 
10.3%
n 53
 
8.9%
e 51
 
8.6%
o 51
 
8.6%
r 44
 
7.4%
l 29
 
4.9%
s 29
 
4.9%
i 24
 
4.0%
t 20
 
3.4%
d 19
 
3.2%
Other values (36) 213
35.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 594
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 61
 
10.3%
n 53
 
8.9%
e 51
 
8.6%
o 51
 
8.6%
r 44
 
7.4%
l 29
 
4.9%
s 29
 
4.9%
i 24
 
4.0%
t 20
 
3.4%
d 19
 
3.2%
Other values (36) 213
35.9%

Company
Text

Distinct99
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2025-03-19T11:10:42.182062image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length31
Median length24.5
Mean length16.99
Min length8

Characters and Unicode

Total characters1699
Distinct characters49
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique98 ?
Unique (%)98.0%

Sample

1st rowRasmussen Group
2nd rowVega-Gentry
3rd rowMurillo-Perry
4th rowDominguez, Mcmillan and Donovan
5th rowMartin, Lang and Andrade
ValueCountFrequency (%)
and 39
 
16.2%
plc 6
 
2.5%
group 6
 
2.5%
llc 6
 
2.5%
ltd 6
 
2.5%
sons 5
 
2.1%
inc 4
 
1.7%
giles 2
 
0.8%
brennan 2
 
0.8%
johnson 2
 
0.8%
Other values (154) 162
67.5%
2025-03-19T11:10:42.965404image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n 162
 
9.5%
a 149
 
8.8%
140
 
8.2%
e 128
 
7.5%
r 116
 
6.8%
o 100
 
5.9%
d 76
 
4.5%
s 71
 
4.2%
t 66
 
3.9%
i 60
 
3.5%
Other values (39) 631
37.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1234
72.6%
Uppercase Letter 258
 
15.2%
Space Separator 140
 
8.2%
Other Punctuation 34
 
2.0%
Dash Punctuation 33
 
1.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 162
13.1%
a 149
12.1%
e 128
10.4%
r 116
9.4%
o 100
 
8.1%
d 76
 
6.2%
s 71
 
5.8%
t 66
 
5.3%
i 60
 
4.9%
l 50
 
4.1%
Other values (14) 256
20.7%
Uppercase Letter
ValueCountFrequency (%)
L 34
13.2%
C 32
12.4%
M 30
11.6%
S 25
9.7%
P 19
 
7.4%
H 19
 
7.4%
G 17
 
6.6%
B 13
 
5.0%
W 11
 
4.3%
A 10
 
3.9%
Other values (12) 48
18.6%
Space Separator
ValueCountFrequency (%)
140
100.0%
Other Punctuation
ValueCountFrequency (%)
, 34
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 33
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1492
87.8%
Common 207
 
12.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 162
 
10.9%
a 149
 
10.0%
e 128
 
8.6%
r 116
 
7.8%
o 100
 
6.7%
d 76
 
5.1%
s 71
 
4.8%
t 66
 
4.4%
i 60
 
4.0%
l 50
 
3.4%
Other values (36) 514
34.5%
Common
ValueCountFrequency (%)
140
67.6%
, 34
 
16.4%
- 33
 
15.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1699
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n 162
 
9.5%
a 149
 
8.8%
140
 
8.2%
e 128
 
7.5%
r 116
 
6.8%
o 100
 
5.9%
d 76
 
4.5%
s 71
 
4.2%
t 66
 
3.9%
i 60
 
3.5%
Other values (39) 631
37.1%

City
Text

Unique 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2025-03-19T11:10:43.498875image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length19
Median length16
Mean length12.38
Min length7

Characters and Unicode

Total characters1238
Distinct characters47
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique100 ?
Unique (%)100.0%

Sample

1st rowEast Leonard
2nd rowEast Jimmychester
3rd rowIsabelborough
4th rowBensonview
5th rowWest Priscilla
ValueCountFrequency (%)
east 12
 
7.6%
south 11
 
7.0%
lake 9
 
5.7%
west 8
 
5.1%
north 7
 
4.5%
new 6
 
3.8%
port 4
 
2.5%
priscilla 1
 
0.6%
chavezborough 1
 
0.6%
ana 1
 
0.6%
Other values (97) 97
61.8%
2025-03-19T11:10:44.266930image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 116
 
9.4%
a 96
 
7.8%
r 93
 
7.5%
t 86
 
6.9%
o 86
 
6.9%
n 74
 
6.0%
i 67
 
5.4%
h 62
 
5.0%
s 60
 
4.8%
57
 
4.6%
Other values (37) 441
35.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1024
82.7%
Uppercase Letter 157
 
12.7%
Space Separator 57
 
4.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 116
11.3%
a 96
9.4%
r 93
 
9.1%
t 86
 
8.4%
o 86
 
8.4%
n 74
 
7.2%
i 67
 
6.5%
h 62
 
6.1%
s 60
 
5.9%
l 47
 
4.6%
Other values (14) 237
23.1%
Uppercase Letter
ValueCountFrequency (%)
S 19
12.1%
E 17
10.8%
J 16
10.2%
N 15
9.6%
L 14
 
8.9%
W 11
 
7.0%
C 9
 
5.7%
A 7
 
4.5%
P 7
 
4.5%
D 6
 
3.8%
Other values (12) 36
22.9%
Space Separator
ValueCountFrequency (%)
57
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1181
95.4%
Common 57
 
4.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 116
 
9.8%
a 96
 
8.1%
r 93
 
7.9%
t 86
 
7.3%
o 86
 
7.3%
n 74
 
6.3%
i 67
 
5.7%
h 62
 
5.2%
s 60
 
5.1%
l 47
 
4.0%
Other values (36) 394
33.4%
Common
ValueCountFrequency (%)
57
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1238
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 116
 
9.4%
a 96
 
7.8%
r 93
 
7.5%
t 86
 
6.9%
o 86
 
6.9%
n 74
 
6.0%
i 67
 
5.4%
h 62
 
5.0%
s 60
 
4.8%
57
 
4.6%
Other values (37) 441
35.6%

Country
Text

Distinct85
Distinct (%)85.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2025-03-19T11:10:44.830012image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length44
Median length26
Mean length11.51
Min length4

Characters and Unicode

Total characters1151
Distinct characters53
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique72 ?
Unique (%)72.0%

Sample

1st rowChile
2nd rowDjibouti
3rd rowAntigua and Barbuda
4th rowDominican Republic
5th rowSlovakia (Slovak Republic)
ValueCountFrequency (%)
islands 8
 
4.9%
and 7
 
4.3%
republic 5
 
3.0%
solomon 4
 
2.4%
the 4
 
2.4%
south 4
 
2.4%
united 4
 
2.4%
saint 3
 
1.8%
zimbabwe 2
 
1.2%
states 2
 
1.2%
Other values (103) 121
73.8%
2025-03-19T11:10:45.672312image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 144
 
12.5%
n 99
 
8.6%
i 93
 
8.1%
e 86
 
7.5%
64
 
5.6%
o 61
 
5.3%
r 60
 
5.2%
t 49
 
4.3%
l 48
 
4.2%
s 46
 
4.0%
Other values (43) 401
34.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 931
80.9%
Uppercase Letter 152
 
13.2%
Space Separator 64
 
5.6%
Dash Punctuation 1
 
0.1%
Open Punctuation 1
 
0.1%
Close Punctuation 1
 
0.1%
Other Punctuation 1
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 144
15.5%
n 99
10.6%
i 93
10.0%
e 86
9.2%
o 61
 
6.6%
r 60
 
6.4%
t 49
 
5.3%
l 48
 
5.2%
s 46
 
4.9%
d 39
 
4.2%
Other values (15) 206
22.1%
Uppercase Letter
ValueCountFrequency (%)
S 25
16.4%
B 13
 
8.6%
I 11
 
7.2%
M 11
 
7.2%
P 10
 
6.6%
A 8
 
5.3%
G 7
 
4.6%
L 7
 
4.6%
T 7
 
4.6%
U 6
 
3.9%
Other values (13) 47
30.9%
Space Separator
ValueCountFrequency (%)
64
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Other Punctuation
ValueCountFrequency (%)
' 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1083
94.1%
Common 68
 
5.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 144
13.3%
n 99
 
9.1%
i 93
 
8.6%
e 86
 
7.9%
o 61
 
5.6%
r 60
 
5.5%
t 49
 
4.5%
l 48
 
4.4%
s 46
 
4.2%
d 39
 
3.6%
Other values (38) 358
33.1%
Common
ValueCountFrequency (%)
64
94.1%
- 1
 
1.5%
( 1
 
1.5%
) 1
 
1.5%
' 1
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1151
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 144
 
12.5%
n 99
 
8.6%
i 93
 
8.1%
e 86
 
7.5%
64
 
5.6%
o 61
 
5.3%
r 60
 
5.2%
t 49
 
4.3%
l 48
 
4.2%
s 46
 
4.0%
Other values (43) 401
34.8%

Phone 1
Text

Unique 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2025-03-19T11:10:46.109445image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length22
Median length19
Mean length15.96
Min length10

Characters and Unicode

Total characters1596
Distinct characters16
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique100 ?
Unique (%)100.0%

Sample

1st row229.077.5154
2nd row5153435776
3rd row+1-539-402-0259
4th row001-808-617-6467x12895
5th row001-234-203-0635x76146
ValueCountFrequency (%)
229.077.5154 1
 
1.0%
001-949-844-8787 1
 
1.0%
1-539-402-0259 1
 
1.0%
001-808-617-6467x12895 1
 
1.0%
001-234-203-0635x76146 1
 
1.0%
283)437-3886x88321 1
 
1.0%
496)452-6181x3291 1
 
1.0%
001-583-352-7197x297 1
 
1.0%
854-138-4911x5772 1
 
1.0%
739.218.2516x459 1
 
1.0%
Other values (90) 90
90.0%
2025-03-19T11:10:46.799048image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 159
10.0%
0 153
9.6%
- 144
9.0%
4 135
8.5%
7 129
8.1%
6 128
8.0%
8 127
8.0%
2 126
7.9%
5 126
7.9%
3 118
7.4%
Other values (6) 251
15.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1296
81.2%
Dash Punctuation 144
 
9.0%
Lowercase Letter 57
 
3.6%
Other Punctuation 40
 
2.5%
Open Punctuation 24
 
1.5%
Close Punctuation 24
 
1.5%
Math Symbol 11
 
0.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 159
12.3%
0 153
11.8%
4 135
10.4%
7 129
10.0%
6 128
9.9%
8 127
9.8%
2 126
9.7%
5 126
9.7%
3 118
9.1%
9 95
7.3%
Dash Punctuation
ValueCountFrequency (%)
- 144
100.0%
Lowercase Letter
ValueCountFrequency (%)
x 57
100.0%
Other Punctuation
ValueCountFrequency (%)
. 40
100.0%
Open Punctuation
ValueCountFrequency (%)
( 24
100.0%
Close Punctuation
ValueCountFrequency (%)
) 24
100.0%
Math Symbol
ValueCountFrequency (%)
+ 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1539
96.4%
Latin 57
 
3.6%

Most frequent character per script

Common
ValueCountFrequency (%)
1 159
10.3%
0 153
9.9%
- 144
9.4%
4 135
8.8%
7 129
8.4%
6 128
8.3%
8 127
8.3%
2 126
8.2%
5 126
8.2%
3 118
7.7%
Other values (5) 194
12.6%
Latin
ValueCountFrequency (%)
x 57
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1596
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 159
10.0%
0 153
9.6%
- 144
9.0%
4 135
8.5%
7 129
8.1%
6 128
8.0%
8 127
8.0%
2 126
7.9%
5 126
7.9%
3 118
7.4%
Other values (6) 251
15.7%

Phone 2
Text

Unique 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2025-03-19T11:10:47.223327image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length22
Median length19
Mean length16.69
Min length10

Characters and Unicode

Total characters1669
Distinct characters16
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique100 ?
Unique (%)100.0%

Sample

1st row397.884.0519x718
2nd row686-620-1820x944
3rd row(496)978-3969x58947
4th row+1-813-324-8756
5th row001-199-446-3860x3486
ValueCountFrequency (%)
397.884.0519x718 1
 
1.0%
855)713-8773 1
 
1.0%
496)978-3969x58947 1
 
1.0%
1-813-324-8756 1
 
1.0%
001-199-446-3860x3486 1
 
1.0%
999-728-1637 1
 
1.0%
1-247-266-0963x4995 1
 
1.0%
001-333-145-0369 1
 
1.0%
1-448-910-2276x729 1
 
1.0%
001-054-401-0347x617 1
 
1.0%
Other values (90) 90
90.0%
2025-03-19T11:10:47.900326image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 175
10.5%
1 171
10.2%
0 161
9.6%
6 147
8.8%
4 145
8.7%
8 134
8.0%
7 124
7.4%
2 119
7.1%
3 117
7.0%
5 112
6.7%
Other values (6) 264
15.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1337
80.1%
Dash Punctuation 175
 
10.5%
Lowercase Letter 64
 
3.8%
Other Punctuation 34
 
2.0%
Open Punctuation 21
 
1.3%
Close Punctuation 21
 
1.3%
Math Symbol 17
 
1.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 171
12.8%
0 161
12.0%
6 147
11.0%
4 145
10.8%
8 134
10.0%
7 124
9.3%
2 119
8.9%
3 117
8.8%
5 112
8.4%
9 107
8.0%
Dash Punctuation
ValueCountFrequency (%)
- 175
100.0%
Lowercase Letter
ValueCountFrequency (%)
x 64
100.0%
Other Punctuation
ValueCountFrequency (%)
. 34
100.0%
Open Punctuation
ValueCountFrequency (%)
( 21
100.0%
Close Punctuation
ValueCountFrequency (%)
) 21
100.0%
Math Symbol
ValueCountFrequency (%)
+ 17
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1605
96.2%
Latin 64
 
3.8%

Most frequent character per script

Common
ValueCountFrequency (%)
- 175
10.9%
1 171
10.7%
0 161
10.0%
6 147
9.2%
4 145
9.0%
8 134
8.3%
7 124
7.7%
2 119
7.4%
3 117
7.3%
5 112
7.0%
Other values (5) 200
12.5%
Latin
ValueCountFrequency (%)
x 64
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1669
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 175
10.5%
1 171
10.2%
0 161
9.6%
6 147
8.8%
4 145
8.7%
8 134
8.0%
7 124
7.4%
2 119
7.1%
3 117
7.0%
5 112
6.7%
Other values (6) 264
15.8%

Email
Text

Unique 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2025-03-19T11:10:48.303313image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length34
Median length29
Mean length22.92
Min length15

Characters and Unicode

Total characters2292
Distinct characters39
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique100 ?
Unique (%)100.0%

Sample

1st rowzunigavanessa@smith.info
2nd rowvmata@colon.com
3rd rowbeckycarr@hogan.com
4th rowstanleyblackwell@benson.org
5th rowcolinalvarado@miles.net
ValueCountFrequency (%)
zunigavanessa@smith.info 1
 
1.0%
alex56@walls.org 1
 
1.0%
beckycarr@hogan.com 1
 
1.0%
stanleyblackwell@benson.org 1
 
1.0%
colinalvarado@miles.net 1
 
1.0%
louis27@gilbert.com 1
 
1.0%
tgates@cantrell.com 1
 
1.0%
asnow@colon.com 1
 
1.0%
mariokhan@ryan-pope.org 1
 
1.0%
mdyer@escobar.net 1
 
1.0%
Other values (90) 90
90.0%
2025-03-19T11:10:49.061352image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 189
 
8.2%
o 187
 
8.2%
a 185
 
8.1%
r 168
 
7.3%
n 164
 
7.2%
c 124
 
5.4%
l 120
 
5.2%
i 112
 
4.9%
m 108
 
4.7%
s 102
 
4.5%
Other values (29) 833
36.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2012
87.8%
Other Punctuation 200
 
8.7%
Decimal Number 46
 
2.0%
Dash Punctuation 34
 
1.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 189
 
9.4%
o 187
 
9.3%
a 185
 
9.2%
r 168
 
8.3%
n 164
 
8.2%
c 124
 
6.2%
l 120
 
6.0%
i 112
 
5.6%
m 108
 
5.4%
s 102
 
5.1%
Other values (16) 553
27.5%
Decimal Number
ValueCountFrequency (%)
8 8
17.4%
6 8
17.4%
7 7
15.2%
2 5
10.9%
4 5
10.9%
5 4
8.7%
9 3
 
6.5%
0 3
 
6.5%
1 2
 
4.3%
3 1
 
2.2%
Other Punctuation
ValueCountFrequency (%)
. 100
50.0%
@ 100
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 34
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2012
87.8%
Common 280
 
12.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 189
 
9.4%
o 187
 
9.3%
a 185
 
9.2%
r 168
 
8.3%
n 164
 
8.2%
c 124
 
6.2%
l 120
 
6.0%
i 112
 
5.6%
m 108
 
5.4%
s 102
 
5.1%
Other values (16) 553
27.5%
Common
ValueCountFrequency (%)
. 100
35.7%
@ 100
35.7%
- 34
 
12.1%
8 8
 
2.9%
6 8
 
2.9%
7 7
 
2.5%
2 5
 
1.8%
4 5
 
1.8%
5 4
 
1.4%
9 3
 
1.1%
Other values (3) 6
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2292
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 189
 
8.2%
o 187
 
8.2%
a 185
 
8.1%
r 168
 
7.3%
n 164
 
7.2%
c 124
 
5.4%
l 120
 
5.2%
i 112
 
4.9%
m 108
 
4.7%
s 102
 
4.5%
Other values (29) 833
36.3%

Subscription Date
Date

Distinct96
Distinct (%)96.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
Minimum2020-01-13 00:00:00
Maximum2022-05-26 00:00:00
Invalid dates0
Invalid dates (%)0.0%
2025-03-19T11:10:49.347670image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-03-19T11:10:49.680198image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Website
Text

Unique 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2025-03-19T11:10:50.133539image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length33
Median length27
Mean length22.64
Min length15

Characters and Unicode

Total characters2264
Distinct characters30
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique100 ?
Unique (%)100.0%

Sample

1st rowhttp://www.stephenson.com/
2nd rowhttp://www.hobbs.com/
3rd rowhttp://www.lawrence.com/
4th rowhttp://www.good-lyons.com/
5th rowhttps://goodwin-ingram.com/
ValueCountFrequency (%)
http://www.stephenson.com 1
 
1.0%
http://www.beck.com 1
 
1.0%
http://www.lawrence.com 1
 
1.0%
http://www.good-lyons.com 1
 
1.0%
https://goodwin-ingram.com 1
 
1.0%
http://www.berger.net 1
 
1.0%
https://www.le.com 1
 
1.0%
https://hammond-ramsey.com 1
 
1.0%
https://www.bullock.net 1
 
1.0%
https://arias.com 1
 
1.0%
Other values (90) 90
90.0%
2025-03-19T11:10:50.854415image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 300
13.3%
t 232
 
10.2%
w 159
 
7.0%
o 150
 
6.6%
. 150
 
6.6%
h 133
 
5.9%
p 115
 
5.1%
s 106
 
4.7%
: 100
 
4.4%
m 99
 
4.4%
Other values (20) 720
31.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1682
74.3%
Other Punctuation 550
 
24.3%
Dash Punctuation 32
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 232
13.8%
w 159
 
9.5%
o 150
 
8.9%
h 133
 
7.9%
p 115
 
6.8%
s 106
 
6.3%
m 99
 
5.9%
c 96
 
5.7%
e 91
 
5.4%
r 82
 
4.9%
Other values (16) 419
24.9%
Other Punctuation
ValueCountFrequency (%)
/ 300
54.5%
. 150
27.3%
: 100
 
18.2%
Dash Punctuation
ValueCountFrequency (%)
- 32
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1682
74.3%
Common 582
 
25.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 232
13.8%
w 159
 
9.5%
o 150
 
8.9%
h 133
 
7.9%
p 115
 
6.8%
s 106
 
6.3%
m 99
 
5.9%
c 96
 
5.7%
e 91
 
5.4%
r 82
 
4.9%
Other values (16) 419
24.9%
Common
ValueCountFrequency (%)
/ 300
51.5%
. 150
25.8%
: 100
 
17.2%
- 32
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2264
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/ 300
13.3%
t 232
 
10.2%
w 159
 
7.0%
o 150
 
6.6%
. 150
 
6.6%
h 133
 
5.9%
p 115
 
5.1%
s 106
 
4.7%
: 100
 
4.4%
m 99
 
4.4%
Other values (20) 720
31.8%

Interactions

2025-03-19T11:10:36.371468image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Missing values

2025-03-19T11:10:36.657232image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
A simple visualization of nullity by column.
2025-03-19T11:10:37.057077image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

IndexCustomer IdFirst NameLast NameCompanyCityCountryPhone 1Phone 2EmailSubscription DateWebsite
01DD37Cf93aecA6DcSherylBaxterRasmussen GroupEast LeonardChile229.077.5154397.884.0519x718zunigavanessa@smith.info2020-08-24http://www.stephenson.com/
121Ef7b82A4CAAD10PrestonLozanoVega-GentryEast JimmychesterDjibouti5153435776686-620-1820x944vmata@colon.com2021-04-23http://www.hobbs.com/
236F94879bDAfE5a6RoyBerryMurillo-PerryIsabelboroughAntigua and Barbuda+1-539-402-0259(496)978-3969x58947beckycarr@hogan.com2020-03-25http://www.lawrence.com/
345Cef8BFA16c5e3cLindaOlsenDominguez, Mcmillan and DonovanBensonviewDominican Republic001-808-617-6467x12895+1-813-324-8756stanleyblackwell@benson.org2020-06-02http://www.good-lyons.com/
45053d585Ab6b3159JoannaBenderMartin, Lang and AndradeWest PriscillaSlovakia (Slovak Republic)001-234-203-0635x76146001-199-446-3860x3486colinalvarado@miles.net2021-04-17https://goodwin-ingram.com/
562d08FB17EE273F4AimeeDownsSteele GroupChavezboroughBosnia and Herzegovina(283)437-3886x88321999-728-1637louis27@gilbert.com2020-02-25http://www.berger.net/
67EA4d384DfDbBf77DarrenPeckLester, Woodard and MitchellLake AnaPitcairn Islands(496)452-6181x3291+1-247-266-0963x4995tgates@cantrell.com2021-08-24https://www.le.com/
780e04AFde9f225dEBrettMullenSanford, Davenport and GilesKimportBulgaria001-583-352-7197x297001-333-145-0369asnow@colon.com2021-04-12https://hammond-ramsey.com/
89C2dE4dEEc489ae0SherylMeyersBrowning-SimonRobersonstadCyprus854-138-4911x5772+1-448-910-2276x729mariokhan@ryan-pope.org2020-01-13https://www.bullock.net/
9108C2811a503C7c5aMichelleGallagherBeck-HendrixElainebergTimor-Leste739.218.2516x459001-054-401-0347x617mdyer@escobar.net2021-11-08https://arias.com/
IndexCustomer IdFirst NameLast NameCompanyCityCountryPhone 1Phone 2EmailSubscription DateWebsite
90915ef6d3eefdD43bENinaChavezByrd-CampbellCassidychesterBhutan053-344-3205+1-330-920-5422x571elliserica@frank.com2020-03-26https://www.pugh.com/
919298b3aeDcC3B9FF3ShaneFoleyRocha-HartSouth DannymouthHungary+1-822-569-0302001-626-114-5844x55073nsteele@sparks.com2021-07-06https://www.holt-sparks.com/
9293aAb6AFc7AfD0fF3CollinAyersLamb-PetersonSouth LonnieAnguilla404-645-5351x012001-257-582-8850x8516dudleyemily@gonzales.biz2021-06-29http://www.ruiz.com/
939454B5B5Fe9F1B6C5SherryYoungLee, Lucero and JohnsonFrankchesterSolomon Islands158-687-1764(438)375-6207x003alan79@gates-mclaughlin.com2021-04-04https://travis.net/
9495BE91A0bdcA49BbcDarrellDouglasNewton, Petersen and MathisDaisyboroughMali001-084-845-9524x1777001-769-564-6303grayjean@lowery-good.com2022-02-17https://banks.biz/
9596cb8E23e48d22EaeKarlGreerCarey LLCEast RichardGuyana(188)169-1674x58692001-841-293-3519x614hhart@jensen.com2022-01-30http://hayes-perez.com/
9697CeD220bdAaCfaDfLynnAtkinsonWare, Burns and OnealNew BradviewSri Lanka+1-846-706-2218605.413.3198vkemp@ferrell.com2021-07-10https://novak-allison.com/
979828CDbC0dFe4b1DbFredGuerraSchmitt-JonesOrtegalandSolomon Islands+1-753-067-8419x7170+1-632-666-7507x92121swagner@kane.org2021-09-18https://www.ross.com/
9899c23d1D9EE8DEB0AYvonneFarmerFitzgerald-HarrellLake ElijahviewAruba(530)311-9786001-869-452-0943x12424mccarthystephen@horn-green.biz2021-08-11http://watkins.info/
991002354a0E336A91A1ClarenceHaynesLe, Nash and CrossJudymouthHonduras(753)813-6941783.639.1472colleen91@faulkner.biz2020-03-11http://www.hatfield-saunders.net/